The Thermomix Data Journey (EN)In the last few years Thermomix by Vorwerk has emerged as the number one IoT kitchen appliance. Complemented by a digital ecosystem it supports customers around the world in the preparation of enjoyable and healthy meals at home every day.On the continuing digital journey of Thermomix, modern, data-driven methodologies have been identified as a promising means to generate new Business insights and boost customer satisfaction. Obviously, a capable data processing infrastructure is a prerequisite for leveraging vast amounts of device and user generated data. In this talk, we will outline our approach to make data generated on the Thermomix device available for data-driven applications and share some lessons we have learnt during the implementation and operation of the various technologies involved. To this end, we will follow the journey of the data from their generation in the appliance, through the pipes and valves of the big data “machine”, up to the visualization and analytics layer.

Working with GPS data in IoT environment from the data science perspective (EN)One of the most common data types to collect in IoT scenarios is GPS data. At Continental we meet those data in many different Use Cases. As Data Scientist we have to handle huge masses of GPS data so we had to develope some methods to handle those data. In this talk we show some of them. Among other it can be shown how to check for quality in GPS data, calculate Kernel densities for Truck tracks, Optimize flawed data using Kalman Filtering and presenting Spatiotemporal data for different use Cases...

ENTFÄLLT - AI + Creativity - why we all need an enterprise muse (EN)Roman Lipski, a renowned painter from Berlin, gets inspired by his Artificial Muse, the first of its kind in the world of art. It is a new kind of symbiosis between man and machine, a dialogue that evolved over the last two years creating not just a new kind of art but step by step a new kind of artist...

Next-Best-Action Marketing with Algorithms (EN)Next-Best-Action (NBA) is known to be the holy grail in marketing. The drastic growth in data volume through digital marketing, as well as the development of new technologies and algorithms lead us closer to the handle. In the presentation we discuss the data science journey for NBA in the context of B2B from drafting an initial concept to running successfull pilots. First we will introduce the idea and goal of NBA and its implications. Starting out from the concept we describe the stepwise development of a solution. The analytical part will be discussed in detail. We will also touch on the toolstack and the technical challenges arrising from it for the implementation. In the end we will present the pilot results. Finally, success factors and pitfalls experienced throughout the project will be highlighted.

Live IoT Use Case demo in E-Commerce Logistics (EN)The “SmartFab Box” system, created by PULS with freely available standard software, transmits measurement data (vital data of a system: in particular voltage and current values, but also temperature or more complex measurement values; similar to the pulse and blood pressure in humans) from the application directly into a cloud. The connection is made independently via LTE from the sensitive company/factory network. In this way, the “vital data” of a machine/system is sent to a cloud in the same way as “Smart Watches”, but with significantly higher security and runtime requirements. Using a dashboard, users can view their data via www.loadprofiling.com in real time, create their own evaluations and export them to standard data formats at any time...

How to get real-time value from your IoT data (EN)An increasing number of IOT devices are producing an ever increasing influx of data. Organizations will have to be ready to handle the volume of data they are facing as well as the other challenges IOT may present. Storage is only half of the problem – how do you get real time value from your IoT data?

Data is the new Oil (EN)Data has become the magic word across the world. “Data is the new oil”. When we talk about data, we should not forget, that, as oil, it should be first harvested, then refined, and only then it can be used, to fuel the engines of the statistical and machine learning systems to generate insights, understand what our customers want, and make correct decisions faster than others.
We at Zalando – one of the biggest online fashion retailers in Europe – are working hard on making data be that oil for us. I will cover the problems of harvesting and understanding data and will talk on where we at Zalando succeed and where we still need to do more progress on making data – the fuel of our future.

Transfer Learning with Convolutional Neural Networks (EN)Over the past 5-10 years there have been huge advances with respect to Artificial Intelligence solutions in the field of Computer Vision. This has largely been driven by a combination of advances in (GPU) processing power, an increase in the amount of high-quality labelled datasets, and innovative new (convolutional) neural network architechtues...

The Thermomix Data Journey (EN)In the last few years Thermomix by Vorwerk has emerged as the number one IoT kitchen appliance. Complemented by a digital ecosystem it supports customers around the world in the preparation of enjoyable and healthy meals at home every day.On the continuing digital journey of Thermomix, modern, data-driven methodologies have been identified as a promising means to generate new Business insights and boost customer satisfaction. Obviously, a capable data processing infrastructure is a prerequisite for leveraging vast amounts of device and user generated data. In this talk, we will outline our approach to make data generated on the Thermomix device available for data-driven applications and share some lessons we have learnt during the implementation and operation of the various technologies involved. To this end, we will follow the journey of the data from their generation in the appliance, through the pipes and valves of the big data “machine”, up to the visualization and analytics layer.

Working with GPS data in IoT environment from the data science perspective (EN)One of the most common data types to collect in IoT scenarios is GPS data. At Continental we meet those data in many different Use Cases. As Data Scientist we have to handle huge masses of GPS data so we had to develope some methods to handle those data. In this talk we show some of them. Among other it can be shown how to check for quality in GPS data, calculate Kernel densities for Truck tracks, Optimize flawed data using Kalman Filtering and presenting Spatiotemporal data for different use Cases...

ENTFÄLLT - AI + Creativity - why we all need an enterprise muse (EN)Roman Lipski, a renowned painter from Berlin, gets inspired by his Artificial Muse, the first of its kind in the world of art. It is a new kind of symbiosis between man and machine, a dialogue that evolved over the last two years creating not just a new kind of art but step by step a new kind of artist...

Next-Best-Action Marketing with Algorithms (EN)Next-Best-Action (NBA) is known to be the holy grail in marketing. The drastic growth in data volume through digital marketing, as well as the development of new technologies and algorithms lead us closer to the handle. In the presentation we discuss the data science journey for NBA in the context of B2B from drafting an initial concept to running successfull pilots. First we will introduce the idea and goal of NBA and its implications. Starting out from the concept we describe the stepwise development of a solution. The analytical part will be discussed in detail. We will also touch on the toolstack and the technical challenges arrising from it for the implementation. In the end we will present the pilot results. Finally, success factors and pitfalls experienced throughout the project will be highlighted.

Live IoT Use Case demo in E-Commerce Logistics (EN)The “SmartFab Box” system, created by PULS with freely available standard software, transmits measurement data (vital data of a system: in particular voltage and current values, but also temperature or more complex measurement values; similar to the pulse and blood pressure in humans) from the application directly into a cloud. The connection is made independently via LTE from the sensitive company/factory network. In this way, the “vital data” of a machine/system is sent to a cloud in the same way as “Smart Watches”, but with significantly higher security and runtime requirements. Using a dashboard, users can view their data via www.loadprofiling.com in real time, create their own evaluations and export them to standard data formats at any time...

How to get real-time value from your IoT data (EN)An increasing number of IOT devices are producing an ever increasing influx of data. Organizations will have to be ready to handle the volume of data they are facing as well as the other challenges IOT may present. Storage is only half of the problem – how do you get real time value from your IoT data?

Data is the new Oil (EN)Data has become the magic word across the world. “Data is the new oil”. When we talk about data, we should not forget, that, as oil, it should be first harvested, then refined, and only then it can be used, to fuel the engines of the statistical and machine learning systems to generate insights, understand what our customers want, and make correct decisions faster than others.
We at Zalando – one of the biggest online fashion retailers in Europe – are working hard on making data be that oil for us. I will cover the problems of harvesting and understanding data and will talk on where we at Zalando succeed and where we still need to do more progress on making data – the fuel of our future.

Transfer Learning with Convolutional Neural Networks (EN)Over the past 5-10 years there have been huge advances with respect to Artificial Intelligence solutions in the field of Computer Vision. This has largely been driven by a combination of advances in (GPU) processing power, an increase in the amount of high-quality labelled datasets, and innovative new (convolutional) neural network architechtues...